Ryhn

I developed a web-based platform for ordering custom photo editing services in vexel art style using the CodeIgniter 3 framework. The website allows users to register, log in, select a service, upload their photo, add special notes, make a payment, and view the final edited result. The platform consists of two roles: admin and user. The admin panel includes CRUD features to manage service categories, design templates, orders, payments, and user data. On the user side, clients can place orders, upload proof of payment, track progress, view final results, and request revisions. Key Features: Service order form with file upload Admin dashboard with full CRUD functionality Automated order & payment status management Responsive and user-friendly design Tech Stack: CodeIgniter , PHP, MySQL, Bootstrap

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This project is an implementation of an Artificial Intelligence model using the Linear Regression method to predict a person’s or organization’s financial expenses based on their income. The model is trained on historical data consisting of income and expense records and is used to map the linear relationship between these two variables. The main goal of this project is to help individuals or organizations manage their finances more efficiently by providing accurate expense predictions based on monthly or yearly income. These predictions can be used for better financial planning, expense control, and identifying consumption patterns.

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This project focuses on developing a hand gesture recognition system using Python and the MediaPipe library. The primary goal is to recognize specific hand gestures and classify them into meaningful actions, such as pointing (index finger), love (thumb, index, and pinky raised), and “you” (pinky finger raised). The system utilizes real-time webcam input to track hand landmarks and applies custom logic to detect gestures based on finger positions. MediaPipe’s Hands module is used to extract 21 key points from the hand, which are then analyzed to determine the status (up/down) of each finger. This project showcases my ability to implement computer vision techniques and apply them creatively in real-world scenarios. It can be used as a foundation for gesture-based control systems, interactive art installations, or accessibility tools. Technologies used: Python OpenCV MediaPipe

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One of my past projects was a class management website designed to help students and lecturers organize assignments, store learning materials, and track attendance efficiently. Built with PHP and Bootstrap, this system provided a user-friendly interface for managing academic activities in a structured and accessible way.

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